如何获取Tensorflow张量尺寸(形状)作为int值?
假设我有一个Tensorflow张量。如何获取张量的尺寸(形状)作为整数值?我知道有两种方法,tensor.get_shape()
和tf.shape(tensor)
,但是我不能将形状值作为整int32
数值。
例如,下面我创建了一个二维张量,我需要获取行数和列数,int32
以便可以调用reshape()
以创建shape张量(num_rows *
num_cols, 1)。但是,该方法tensor.get_shape()
返回值作为Dimension
类型,而不是类型int32
。
import tensorflow as tfimport numpy as np
sess = tf.Session()
tensor = tf.convert_to_tensor(np.array([[1001,1002,1003],[3,4,5]]), dtype=tf.float32)
sess.run(tensor)
# array([[ 1001., 1002., 1003.],
# [ 3., 4., 5.]], dtype=float32)
tensor_shape = tensor.get_shape()
tensor_shape
# TensorShape([Dimension(2), Dimension(3)])
print tensor_shape
# (2, 3)
num_rows = tensor_shape[0] # ???
num_cols = tensor_shape[1] # ???
tensor2 = tf.reshape(tensor, (num_rows*num_cols, 1))
# Traceback (most recent call last):
# File "<stdin>", line 1, in <module>
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1750, in reshape
# name=name)
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 454, in apply_op
# as_ref=input_arg.is_ref)
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 621, in convert_to_tensor
# ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 180, in _constant_tensor_conversion_function
# return constant(v, dtype=dtype, name=name)
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 163, in constant
# tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape))
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 353, in make_tensor_proto
# _AssertCompatible(values, dtype)
# File "/usr/local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 290, in _AssertCompatible
# (dtype.name, repr(mismatch), type(mismatch).__name__))
# TypeError: Expected int32, got Dimension(6) of type 'Dimension' instead.
回答:
要将形状显示为整数列表,请执行tensor.get_shape().as_list()
。
要完成tf.shape()
通话,请尝试tensor2 = tf.reshape(tensor,
tf.TensorShape([num_rows*num_cols, 1]))。或者,您可以直接tensor2 = tf.reshape(tensor,
tf.TensorShape([-1, 1]))在可以推断出其第一维的地方进行操作。
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